Diagnostic assistance, quantification, characterization, image reconstruction: medical artificial intelligence at your fingertips for radiology.
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US2.AI

AI solution for echo cardiography analysis

Discover

Us2.ai software recognizes and analyzes transthoracic 2D and Doppler modality echocardiogram images, automating cardiac structural and functional measurements. Us2 algorithms produce a complete patient report, with editable annotations, and findings based upon international reference guidelines

Late diagnosis of heart failure (HF) remains a serious issue, despite the availability of effective treatments when caught early. While echocardiography is the most commonly used imaging tool, it presents several challenges: - Time-Consuming: The process is slow and can take considerable time. - Inconsistent Results: Results can vary significantly, even among trained professionals. - High Cost: Equipment and software are expensive. - Limited Accessibility: Primary care facilities often lack access to echocardiography. Furthermore, a global shortage of sonographers has led to high demand for their expertise, driving up costs. These exams are also time-intensive, contributing to long patient waitlists and exposing staff to potential repetitive strain injuries.
US2.AI

A full suite of measurements

US2.AI provides over 45 fully automated echocardiography measurements, such as ejection fraction, strain for the left atrium and right ventricle, and more—all without the need for ECG. It offers comprehensive analysis, covering strain and regional strain imaging, 2D, and Doppler views. With true AI automation, there’s no need for manual frame selection, annotations, or view selection—just seamless, automated insights.


Disease Condition Detection

US2.AI can evaluate heart disease conditions, including heart failure (HFpEF, HFmrEF, HFrEF), pulmonary hypertension & right-heart failure, hypertrophic cardiomyopathy, amyloidosis, valvular disease (stenosis, regurgitations), Ischemic heart disease, and more.


Time gains: AI echo reduces exam time by 70% (6)

Early detection of cardiological risk factors (9)

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Publications

  1. A Ioannou, et al, Automated analysis of echocardiograms at diagnosis is able to predict prognosis in ATTR cardiomyopathy, European Heart Journal - Cardiovascular Imaging, Volume 24, Issue Supplement_1, June 2023
    P Myhre, et al, External validation of a deep learning algorithm for automated echocardiographic strain measurements, European Heart Journal - Cardiovascular Imaging, Volume 24, Issue Supplement_1, June 2023
    Krishna H, et al. Fully Automated Artificial Intelligence Assessment of Aortic Stenosis by Echocardiography. J Am Soc Echocardiogr. 2023 Jul;36(7):769-777

  2. Tromp J, Seekings PJ, Hung CL, Iversen MB, Frost MJ, Ouwerkerk W, Jiang Z, Eisenhaber F, Goh RSM, Zhao H, Huang W, Ling LH, Sim D, Cozzone P, Richards AM, Lee HK, Solomon SD, Lam CSP, Ezekowitz JA. Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study. Lancet Digit Health. 2022 Jan;4(1):e46-e54. doi: 10.1016/S2589-7500(21)00235-1. Epub 2021 Dec 1. PMID: 34863649.

  3. Myhre PL, Tromp J, Ouwerkerk W, Ting DSW, Docherty KF, Gibson CM, Lam CSP. Digital tools in heart failure: addressing unmet needs. Lancet Digit Health. 2024 Oct;6(10):e755-e766. doi: 10.1016/S2589-7500(24)00158-4. Epub 2024 Aug 29. Erratum in: Lancet Digit Health. 2024 Oct;6(10):e680. doi: 10.1016/S2589-7500(24)00201-2. PMID: 39214764.

  4. Tromp J, Bauer D, Claggett BL, Frost M, Iversen MB, Prasad N, Petrie MC, Larson MG, Ezekowitz JA, Solomon SD. A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram. Nat Commun. 2022 Nov 9;13(1):6776. doi: 10.1038/s41467-022-34245-1. PMID: 36351912; PMCID: PMC9646849.

  5. Huang W, Koh T, Tromp J, Chandramouli C, Ewe SH, Ng CT, Lee ASY, Teo LLY, Hummel Y, Huang F, Lam CSP. Point-of-care AI-enhanced novice echocardiography for screening heart failure (PANES-HF). Sci Rep. 2024 Jun 12;14(1):13503. doi: 10.1038/s41598-024-62467-4. PMID: 38866831; PMCID: PMC11169397.

  6. Sadeghpour A, Jiang Z, Hummel YM, Frost M, Lam CSP, Shah SJ, Lund LH, Stone GW, Swaminathan M, Weissman NJ, Asch FM. An Automated Machine Learning-Based Quantitative Multiparametric Approach for Mitral Regurgitation Severity Grading. JACC Cardiovasc Imaging. 2024 Aug 2:S1936-878X(24)00247-X. doi: 10.1016/j.jcmg.2024.06.011. Epub ahead of print. PMID: 39152959.

  7. Hirata Y, Nomura Y, Saijo Y, Sata M, Kusunose K. Reducing echocardiographic examination time through routine use of fully automated software: a comparative study of measurement and report creation time. J Echocardiogr. 2024 Sep;22(3):162-170. doi: 10.1007/s12574-023-00636-6. Epub 2024 Feb 3. PMID: 38308797; PMCID: PMC11343801.

  8. K Teramoto et al. Abstract 9620: External Validation of Deep Learning-Based Echocardiography Algorithms to Automate View Selection and Annotation of the Echocardiogram. Circulation, Volume 146, Number Suppl_1 https://doi.org/10.1161/circ.146.suppl_1.9620

  9. Valsaraj A, Kalmady SV, Sharma V, Frost M, Sun W, Sepehrvand N, Ong M, Equilbec C, Dyck JRB, Anderson T, Becher H, Weeks S, Tromp J, Hung CL, Ezekowitz JA, Kaul P. Development and validation of echocardiography-based machine-learning models to predict mortality. EBioMedicine. 2023 Apr;90:104479. doi: 10.1016/j.ebiom.2023.104479. Epub 2023 Feb 28. PMID: 36857967; PMCID: PMC10006431.

Regulatory

Us2 medical device is a regulated health product that bears the CE mark, Class IIb. Notified Body: BSI. n°2797. Manufacturer: EKO.AI PTE.LTD. Us2 is a diagnostic tool and shall not be used alone to recommend medical care for diagnostic purposes. Please read the instructions in the user manual carefully. Please contact contact@incepto-medical.com for more information. Last update: 2024/11/27

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Publisher

Us2.ai was founded in 2017 by Dr Carolyn Lam, James Hare & Dr Yoran Hummel. The company specializes in Artificial Intelligence and is dedicated to automating the fight against heart disease through the development of deep learning solutions applied to ultrasound medical imaging biomarkers. Us2.ai is a fast-growing startup backed by IHH Healthcare, Heal Partners, Sequoia India and EDBI.
Us2.ai mission is to improve patient outcomes and expand healthcare access by democratizing echocardiograms – the most commonly used tool for the detection of heart risk – through the use of AI. Us2.ai is building a future where everyone, from the most advanced tech-driven regions to the most resource-constrained communities, can have equal access to high quality, consistent and inexpensive echo analysis.